Platform bans cannot prevent rivals from distilling superior model outputs to train their own.
Lagging AI developers quietly bypass platform bans to train their models on the outputs of superior competitors while claiming independent technology.
The same conclusion keeps arriving from across the workspace's research — 1 topics independently instantiate this theme. Filter the evidence by where it came from:
xAI bypassed regulatory boundaries and competitive restrictions to train its model on outputs distilled from a superior competitor's model.
Hosting a competitor's workloads on adjacent hardware provides operational visibility that helps the landlord study and run the competitor's high-value model patterns.
It presents high-profile political and corporate friction stemming from accusations that lagging labs train their competitive models on distilled outputs of superior U.S. systems.
It demonstrates how a developer bypassed API bans to continue distilling a competitor's model outputs to train its own systems.
This shows competitors bypassing trade and platform constraints by distilling outputs from superior models to train their own.
Chinese AI labs bypassed platform security and geographic restrictions to systematically distill high-quality outputs from leading Western models.
Allegations that Z.ai's near-frontier GLM-5.2 was trained by distilling outputs from Google and Anthropic models illustrate the futility of platform constraints in preventing model logic capture.